A Web-based System for Optimizing Post Disaster Temporary Housing Allocation

Abstract:

Natural catastrophes can result in large scale displacement of populations, who are in urgent need of temporary quarters until permanent housing can be provided. During this period, the temporary housing plays an important role in the families' physical, psychological, social and economic recovery. A number of research studies have addressed this specific temporary housing problem and aimed at identifying the optimal temporary housing arrangements, but few used quantitative methods to incorporate the displaced families' specific socioeconomic needs and housing preferences. From the decision makers' perspective, current temporary housing practices often result in high cost, late delivery and frequent family complaints caused by improper allocation. The scale and complexity of the problem requires strategic planning and a fast decision support system. The main objective of this thesis is to present a way of effectively matching available temporary housing resources to displaced families' social, economic and psychological needs with the minimum required public expenditure. A new web-based post disaster temporary housing management system is developed to accomplish this task. It fully considers individual family's specific needs and provides comprehensive decision support. The web-based system first solicits and stores the data from potential housing providers. It applies Google Map® in the user interface to facilitate data acquisition. The collected families' needs and preferences are then translated into a socioeconomic index to evaluate housing alternatives. In order to maximize overall families' utility and minimize expenditure, a multi-objective optimization module is formulated using the classic weighted sum method. A customized Hungarian Algorithm is developed to solve the optimization problem. In addition, the system also provides decision support for the total cost and overall socioeconomic benefit trade off and cost-benefit analysis for various potential housing. The web-based system can significantly improve the current temporary housing practices. It has a user friendly interface and allows families to better describe their requirements. With the customized Hungarian Algorithm the optimization process won't cause computer out of memory in the large scale problems and it saves significant running time. The computational speed and efficiency of the system enables its use in the response phase following a disaster, where it can offer high quality allocation solutions with low cost.